What role does AI play in evolving your digital art style?

I suppose stealing art from others and claiming it as your own is always a potential game changer, so long as nobody finds you out and you get away with it. The world has always had its fair share of talentless wannabes. AI enables this at scale.

I have an artistic background with a master in engineering and was introduced to AI while trying to figure out how to use technology for my art. In September 2022 I saw my technologist friends start creating spectacular images and calling themselves "Artists" without ever having had a pencil in their hand. The first thing I felt as an artist was frustration. But for the last few years I've been working with Generative AI trying to understand what kind of technology it is. I firmly believe that generative artificial intelligence can be a new tool for art. Of course, we are only at the beginning of this evolution, and perhaps artists will use these AI tools in new ways that we can't currently imagine.

AI helps me with brainstorming and with coming up with new ideas for my non-AI art. It’s a great tool to ideate fast before spending time and material on physical pieces of art.

AI plays a significant role in evolving digital art styles by providing artists with new tools, techniques, and inspirations. AI algorithms can analyze vast amounts of artistic data, including images, styles, and techniques, to generate novel and unique visual elements. For example, AI-powered style transfer can apply the aesthetic qualities of one image or art style to another, allowing artists to experiment with different artistic expressions. Generative adversarial networks (GANs) can create entirely new artworks based on learned patterns and styles, pushing the boundaries of creativity.

I worked as a photographer and love using my old creations as a style reference for my images. Also currently learning 3D and it’s a great way to direct AI models. Love combining all art forms I enjoy.

It takes no part at all. If you want create, then create. If you want to create a facsimile or a concept art composition then, I guess AI is what you'd want.

✬ A transferência de estilo não é apenas a aplicação de um filtro. É a criação de uma sinfonia de estilos, onde cada pincelada, cada forma, cada textura se unem em uma composição única, uma conversa visual entre diferentes movimentos artísticos. ✬ Experimente combinar estilos de diferentes épocas, culturas e movimentos artísticos. Crie uma obra que transita entre o realismo e o abstrato, o clássico e o moderno, o figurativo e o não figurativo. ✬ Deixe que a "conversa" entre os estilos revele novas formas de expressão. #ai #ia

En el caso de artistas con un marcado estilo, como el que tenía Picasso por ejemplo, se podría realizar un fine tunning con obras previas de ese autor. De esa manera, podemos pedir al modelo que genere imágenes basándose en el estilo de las anteriores obras, facilitando así aún más el trabajo inicial del artista.

Style transfer algorithms enable artists to seamlessly blend different artistic styles, creating unique and captivating visual compositions. By leveraging deep learning techniques, AI algorithms can extract stylistic features from reference images and apply them to original artworks, transforming their appearance while preserving underlying structures. This enables artists to explore hybrid aesthetics, combining elements from diverse artistic traditions to create compelling and visually striking compositions.

﹅ Os algoritmos generativos não são apenas ferramentas para gerar formas e texturas aleatórias. Eles são como parceiros de dança, oferecendo movimentos inesperados, novas possibilidades de composição e um ritmo único, que você pode controlar e moldar de acordo com sua visão. ﹆ A arte digital, nesse contexto, se transforma em uma dança entre razão e caos, onde o artista trabalha com o imprevisível, com o "erro" como elemento de beleza, com a aleatoriedade como ferramenta de expressão. ﹅ A IA não substitui sua criatividade, mas a amplia, a desafia, a empurra para novos limites de expressão! #ai #ia

Los modelos de IA no solo pueden ayudar a generar la base completa de la obra, si no que también se pueden usar para generar partes concretas de la obra o incluso para crear determinadas fusiones o situaciones surrealistas. Otro uso puede ser el de generar mezclas de colores que concuerden con la obra que se está realizando, los elementos que en ella aparecen y el estilo del autor.

AI-driven creative algorithms empower artists to explore unconventional techniques and experiment with novel artistic approaches. From generative adversarial networks (GANs) to variational autoencoders (VAEs), these algorithms facilitate the generation of original artwork based on predefined parameters or constraints. Artists can harness these tools to generate abstract compositions, surreal landscapes, or even interactive multimedia experiences, pushing the boundaries of traditional artistic practice.

The concept of generative algorithms in digital art is indeed a compelling intersection of technology and creativity. What's particularly fascinating is the ability for artists to adjust the parameters of these algorithms, effectively balancing between randomness and structured design. This synergy of human creativity and algorithmic efficiency not only enhances artistic expression but also introduces a new aesthetic that marries precision with the beauty of imperfection. As we explore these possibilities, it's intriguing to consider how similar principles could be applied in other creative fields, including legal design, where the blend of systematic logic and creative problem-solving is crucial.

True some of the use cases of Creative Algorithms include : Art Creation: Algorithms can generate paintings, sculptures, and other forms of visual art. Music Composition: AI can compose music in various genres, assisting or even replacing human composers in some contexts. Writing and Storytelling: Algorithms can generate prose and poetry, aiding writers or producing content autonomously. Game Design: Procedural generation is used to create levels, characters, and entire game worlds dynamically. Product Design: Evolutionary algorithms optimize designs for functionality and aesthetics

AI significantly enhances the iterative process in art creation by enabling the rapid generation of theme variations. This capability allows artists to explore multiple avenues swiftly, a process that would typically take much longer manually. Artists can then select the most promising directions for further refinement. This AI-powered iterative loop fosters a dynamic evolution of art style, permitting artists to adapt and integrate new influences quickly and efficiently.

• GANs (Generative Adversarial Networks): Utilize generator and discriminator networks to create and refine realistic images. Example: Refik Anadol's data-driven installations using urban data. • Style Transfer: Apply neural network techniques to blend styles of different images. Example: DeepArt transforms photos using famous painting styles. • Reinforcement Learning in Art: Optimise art creation via reward-based AI training. Example: Mario Klingemann's evolving generative art. • Real-Time Feedback Systems: Tools like Adobe Sensei provide real-time artistic enhancement suggestions. • Collaborative Art Platforms: Artbreeder enables users to iteratively blend and modify images collectively.

💡Cada imagen generada por un modelo de IA tiene un parámetro llamado "seed". Este parámetro es una referencia del patrón inicial que se ha usado para generar la imagen resultante. Si queremos obtener una imagen similar a la obtenida, podemos obtener la seed de la primera imagen generada y pasarla como parámetro en el prompt de la siguiente imagen. Esto nos generaría una imagen similar a la primera, pero sin ser igual.

AI facilitates an iterative approach to artistic creation, enabling artists to refine and evolve their digital art styles over time. By leveraging feedback loops and adaptive learning algorithms, artists can iteratively refine their techniques, incorporating insights gained from experimentation and audience feedback. This iterative process of creation and refinement allows artists to continuously push the boundaries of their artistic vision, evolving their digital art styles in response to changing trends and personal growth.

Iterative evolution harnesses the combined power of human creativity and computational algorithms, making it a potent tool for generating innovative and user-tailored solutions across various domains. but there are few challenges and considerations: 1. Users may get tired of repetitive iterations or evaluations 2. Handling large populations can be complex and multiple user feedback is sometimes unmanageable 3. User preferences can Bias the evaluation 4. Translating user feedback into a fitness function that guides the algorithm can be problematic

⭐ La facilidad para generar "ideas bases" otorga a los artistas una gran ventaja competitiva, ya que les permite generar diferentes ideas, presentarlas a sus clientes y ver cuál es la que más gusta. 👉🏼 Una vez descubierta cuál es la imagen que más interés despierta, puede trabajar a fondo en el desarrollo completo de ella, pero sabiendo previamente que esa idea gusta y hay personas interesadas en ella, lo que facilita su posterior venta y optimiza su trabajo.

Data-driven decision-making plays a crucial role in the evolution of digital art styles, enabling artists to make informed choices based on empirical evidence and quantitative analysis. AI algorithms analyze vast repositories of artistic data, including sales metrics, audience demographics, and social media engagement metrics, providing valuable insights into market trends and audience preferences. Armed with this data, artists can tailor their artistic practices to better resonate with their target audience, optimizing their creative output for maximum impact and relevance.

When Generative AI software was born in September 2022, there was a desire to break the static creativity of art all over the world. We opted to work on a type of creativity that we can define as "Shared Creativity". We agreed to stay on the same platforms and share the images that we generated, with the aim of improving these software and guiding them where we wanted. So it is true that a new type of creativity has been generated.

I've been using my AI, a superscaled, custom-modified version of Google's "DeepDream" (part of a computer vision system tasked with image recognition) since early 2016 as a collaborative partner that provides a unique way of "seeing" the landscapes that I've captured via computational photography techniques (see dreamscapes.ai). While I can set the aesthetic direction in which my AI interprets my photograph images, I can't control the details. The results inevitably surprise and delight me... and I hope communicate my core thesis, which is that the world is not what we see; it's the way we see.

AI fosters collaboration and community-building among digital artists, enabling collective exploration and co-creation of digital art styles. Through online platforms, social media communities, and collaborative projects, artists can share ideas, collaborate on projects, and collectively push the boundaries of digital artistry. AI-powered collaboration tools facilitate real-time collaboration, enabling artists to work together seamlessly regardless of geographical barriers or time constraints.

Without a doubt, AI is contributing to a Renaissance in art and design. With a detailed prompt, AI can create images ranging in style from black and white sketch to photorealistic style images. The new ChatGPT4o is a terrific collaborative partner for art and conceptual art. People who have ideas but who have not had the skill to express them are not able to produce some excellent images. I like Microsoft Image Maker and Ideogram, both of which are free to use. As with all of AI, learning how to prompt is key to getting excellent results.

AI can enable interactive and collaborative art creation. Tools like Google's DeepDream and various AI painting applications allow users to interact with the AI in real-time, creating art pieces that are a blend of human creativity and machine learning.

The evolution of digital art styles is powered by the collective efforts of AI technology and the insights shared by the vibrant LinkedIn community. Cisco's sponsorship of Artificial Intelligence (AI) collaborative articles underscores the importance of collaborative innovation and knowledge sharing in driving the evolution of digital artistry. By harnessing the power of AI and leveraging the collective wisdom of the LinkedIn community, we can unlock new creative possibilities and shape the future of digital art.

AI is a powerful tool that can significantly influence and evolve digital art styles. By providing new sources of inspiration, automating repetitive tasks, offering personalized feedback, and enabling interactive and collaborative creation, AI helps artists push the boundaries of their creativity and continuously develop their unique artistic expressions.

AI can enhance your digital art style by providing creative inspiration, increasing efficiency, and expanding capabilities. I've summarized my thinking: Creative Inspiration: Use AI for generative art and style transfer to explore new aesthetics Efficiency: Automate repetitive tasks and get smart suggestions Skill Enhancement: Learn new techniques from AI outputs and collaborate with AI for innovative results Expanding Capabilities: Utilize AI for 3D modelling, AR, and VR Personalization: Customize tools + analyze audience feedback New Mediums: Experiment with digital sculpting and interactive art Market Analysis: Predict trends and understand audience preferences AI as a Medium: Create AI-generated and algorithmic art Pls Like&repost-TY!